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function, and this will lead to di erent actions altogether We might, for instance, wish instead to separate the sh based on their sex all females (of either species) from all males if we wish to sell roe Alternatively, we might wish to cull the damaged sh (to prepare separately for cat food), and so on Di erent decision tasks may require features and yield boundaries quite di erent from those useful for our original categorization problem This makes it quite clear that our decisions are fundamentally task or cost speci c, and that creating a single general purpose arti cial pattern recognition device ie, one capable of acting accurately based on a wide variety of tasks is a profoundly di cult challenge This, too, should give us added appreciation of the ability of humans to switch rapidly and uidly between pattern recognition tasks.

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38 has information on the pty (pseudo-terminal) module, its fork and spawn functions, and the os.forkpty function.

Coating Pan capacity, inlet/exhaust temperatures, Pan Speed, spray rate, Air flow rate, Bed temperature Dissolution, disintegration, coating weight gain, mottling, assay/ potency

Since classi cation is, at base, the task of recovering the model that generated the patterns, di erent classi cation techniques are useful depending on the type of candidate models themselves In statistical pattern recognition we focus on the statistical properties of the patterns (generally expressed in probability densities), and this will command most of our attention in this book Here the model for a pattern may be a single speci c set of features, though the actual pattern sensed has been corrupted by some form of random noise Occasionally it is claimed that neural pattern recognition (or neural network pattern classi cation) should be considered its own discipline, but despite its somewhat di erent intellectual pedigree, we will consider it a close descendant of statistical pattern recognition, for reasons that will become clear.

Monthly user Busy hour User BH data User BH Total data Size Units data (number (BH) usage (events per data rate per user per (kB) of events per (%) user in BH) (kb/s) BH (kB) user per month) 50 100 62.5 50 750 17 17 17 17 20 0.28 0.57 0.35 0.28 5 0.04 0.03 0.09 0.06 0.56 0.78 17 11.33 42.5 28.33 250 349.17 60 20 120 100 50 MMS Email Webpage download Media le download WAP pages

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To create a new drawing based on a template, choose File New to open the Select Template dialog box, which lists all the available templates, as shown in Figure 2-1. Click any template to see its preview, if any. Double-click a template to create a new drawing based on that template. Because AutoCAD or AutoCAD LT opens with Drawing1.dwg, the new drawing is named Drawing2.dwg. Subsequent drawings that you create are named Drawing3.dwg and so on. When you save and name your drawing, the original template file is unaffected. The QNEW command is useful if you always start a new drawing based on the same template. You set a default template and then click QNew on the Standard toolbar to start a new drawing immediately, based on that default template. To set the default template, follow these steps: 1. Choose Tools Options and click the Files tab. 2. Double-click the Template Settings item. 3. Double-click the Default Template File Name for QNEW item.

If instead the model consists of some set of crisp logical rules, then we employ the methods of syntactic pattern recognition, where rules or grammars describe our decision For example we might wish to classify an English sentence as grammatical or not, and here statistical descriptions (word frequencies, word correlations, etc) are inapapropriate It was necessary in our sh example to choose our features carefully, and hence achieve a representation (as in Fig 16) that enabled reasonably successful pattern classi cation A central aspect in virtually every pattern recognition problem is that of achieving such a good representation, one in which the structural relationships among the components is simply and naturally revealed, and one in which the true (unknown) model of the patterns can be expressed.